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Downloaded from the Gene Expression Omnibus to Uncover Diferentially Expressed Long Non-Coding Rnas (Lncrnas), Mrnas, and Micrornas (Mirnas) Shi and Yao BMC Med Genomics (2021) 14:133 https://doi.org/10.1186/s12920-021-00931-0 RESEARCH ARTICLE Open Access Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis Qinghong Shi1 and Hanxin Yao2* Abstract Background: Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods: Expression profles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover diferentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results: In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were signifcantly diferentially expressed. The ceRNA regu- latory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinosi- tol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM- related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion: The identifed signature RNAs may serve as important regulators in the pathogenesis of T1DM. Keywords: T1DM, LncRNAs, CeRNAs Background of T1DM is rising worldwide, with more than 80% of dia- Recently, type 1 diabetes mellitus (T1DM) is a multi- betes occurring in younger children [2, 3]. factorial autoimmune disease characterized by insulin Many eforts have been made recently to gain insights defciency and hyperglycaemia, which is considered to into the pathogenesis of T1DM. Tree main regions on involve the selective attack of insulin-producing pancre- chromosomes, including the protein tyrosine-phos- atic β cells by activated T lymphocytes that recognize phatase non-receptor-type 22 region on chromosome their autoantigens [1]. T1DM accounts for approximately 1p13, the human leukocyte antigen region on chro- 5–10% of all cases of diabetes mellitus, and the incidence mosome 6p21, and the insulin region on chromosome 11p15, play essential roles in insulin expression, immune *Correspondence: [email protected] response, and β-cell function, which are associated with 2 Department of Clinical Laboratory, The First Hospital of Jilin University, T1DM [4, 5]. More than 50 genomic risk loci have been No. 1, Xinmin Street, Chaoyang District, Changchun 130021, Jilin, China identifed for T1DM based on genome-wide association Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Shi and Yao BMC Med Genomics (2021) 14:133 Page 2 of 10 studies [5]. However, most of the risk loci are located in profles retrieved from the Gene Expression Omnibus non-coding genomic regions, and an increasing num- [17]. Subsequently, ceRNA-based transcriptional sig- ber of studies have focused on the potential roles of natures were revealed via the construction of a T1DM- long non-coding RNAs (lncRNAs) in pancreatic islets related ceRNA regulatory network. and the pathogenesis of T1DM [6, 7]. Motterle et al. found that some lncRNAs are modulated by proinfam- Methods matory cytokines during the development of T1DM in Data source and annotation non-obese diabetic mice, which probably contributes to Expression and non-coding RNA profles (GEO accession the sensitization of β cells to apoptosis and failure dur- number: GSE55100) deposited by Yang et al. [16] were ing the initial phases of T1DM [7]. Te nuclear-enriched downloaded from the National Center for Biotechnol- β-cell lncRNA PLUTO may regulate the expression of ogy Information GEO (https:// www. ncbi. nlm. nih. gov/ PDX1, which is a key pancreatic β-cell transcription fac- geo/) [18], which consist of two subseries, GSE55098 and tor; furthermore, knockdown of PLUTO is associated GSE55099. Te GSE55098 contains expression data of with the downregulation of PDX1 in EndoC-βH1 cells peripheral blood mononuclear cells from 12 patients with and primary islet cells, implicating the roles of lncRNAs T1DM and 10 normal control subjects, which were based in the regulation of β-cell-specifc transcription factors on the GPL570 [HG-U133_Plus_2] Afymetrix Human [8]. Terefore, examining the ability of lncRNAs to regu- Genome U133 Plus 2.0 Array platform. Te GSE55099 late gene expression and cell-specifc transcription fac- contains microRNA expression data from peripheral tors opens avenues to a better understanding of T1DM blood mononuclear cells from the same 12 patients with pathogenesis. T1DM and 10 normal control subjects, based on the On the other hand, an increasing body of evidence indi- GPL8786 [miRNA-1] Afymetrix Multispecies miRNA-1 cates that microRNAs (miRNAs) play important roles in Array platform. Te miRNAs, lncRNAs, and mRNAs in processes involved in the pathogenesis of T1DM, includ- the downloaded profles were annotated via the Human ing immune system functions and β-cell metabolism and Genome Organization Gene Nomenclature Committee death [9, 10]. Assmann et al. have suggested that 11 cir- (http:// www. genen ames. org/) [19], where over 40,000 culating miRNAs (miR-21-5p, miR-24-3p, miR-100-5p, approved gene symbols have been recorded, of which miR-146a-5p, miR-148a-3p, miR-150-5p, miR-181a-5p, more than 19,000 are for protein-coding genes. miR-210-5p, miR-342-3p, miR-375, and miR-1275) are consistently dysregulated in T1DM patients [11]. It has Identifcation of diferentially expressed RNAs been further revealed that fve miRNAs (miR-103a-3p, Te diferentially expressed RNAs (DERs) between miR-155-5p, miR-200a-3p, miR-146a-5p, and miR- T1DM and normal controls were screened with Limma 210-3p), which have been confrmed as dysregulated (Linear Models for Microarray Data) package (Version miRNAs based on plasma miRNA expression profles of 3.34.0; https:// bioco nduct or. org/ packa ges/ relea se/ bioc/ T1DM patients and control individuals, could regulate html/ limma. html) [20] of R3.4.1. Te cut-of criteria genes involved in the innate immune system-, MAPK-, were set as false discovery rate (FDR) less than 0.05 and apoptosis-, insulin-, and cancer-related pathways [12]. |log2 fold change| greater than 0.5. Two-way hierarchi- Additionally, it is widely acknowledged that competing cal clustering analysis based on Euclidean distance was endogenous RNAs (ceRNAs) can interact with mRNAs executed for all the identifed DERs via the pheatmap by competing with miRNAs, and miRNA-mediated (Version 1.0.8, https:// cran.r- proje ct. org/ web/ packa ges/ interactions between lncRNAs and mRNAs occur in pheat map/ index. html) of R3.4.1 [21–23]. Meanwhile, the progression of various diseases [13–15]. However, gene ontology (GO) functional enrichment in terms of few current studies have reported on the ceRNA-based biological process as well as Kyoto Encyclopedia of Genes regulatory mechanisms of T1DM. In the study of Yang and Genomes (KEGG) pathway enrichment analysis were et al. [16] global miRNA and mRNA expressions were conducted for diferentially expressed mRNAs via the profled in peripheral blood mononuclear cells from 12 Database for Annotation, Visualization and Integrated patients with newly diagnosed T1DM and 10 normal Discovery (DAVID, Version 6.8, https:// david. ncifc rf. controls, while miRNA-mediated interactions between gov/) [24, 25], with a threshold of p < 0.05. lncRNAs and mRNAs were not revealed. Tus, further studies aimed at clarifying ceRNA-based transcriptional Construction of ceRNA regulatory network signatures are needed to provide new insights into the Te regulatory interactions between diferentially pathogenesis of T1DM. In our present study, diferen- expressed lncRNAs and miRNAs were retrieved from tially expressed lncRNAs, mRNAs, and miRNAs between the DIANA-LncBase (Version 2, http:// carol ina. imis. T1DM and normal controls were identifed based on athena- innov ation. gr/ diana_ tools/ web/ index. php) [17]. Shi and Yao BMC Med Genomics (2021) 14:133 Page 3 of 10 Te negative regulatory interactions with a miRNA tar- Results get gene score (miTG-score) larger than 0.6 (the default Data annotation and DER screening threshold in DIANA-LncBase) were retained to con- According to the platform annotation information, struct the lncRNA–miRNA regulatory network, which 946 lncRNAs, 597 miRNAs, and 10,085 mRNAs were was visualized with Cytoscape (Version 3.6.1, https:// received.
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